Smartphone-Based Retinal Camera Rig for AI Screening

A blog and description of a smartphone system used for AI retinal imaging

Image by Author

Recently, I completed a project for my organization, Drishti, which performs AI-based Diabetic Retinopathy screening for rural areas in Bangladesh. To take retinal scans without full-cost retinal cameras, we built a rig that can house a smartphone to take these images. The images can then be uploaded to our research-backed AI algorithm to provide instant and accurate initial screening. This project demonstrates the harmony between software and hardware, as we were able to effectively integrate our AI algorithm with the low-cost retinal camera rig. Hopefully you enjoy this article, and if you have any thoughts or areas of improvement, please let me know.

Software

Model Schematic of our CNN (Image by Author)

Our algorithm is a CNN that performs Diabetic Retinopathy screening. The algorithm itself prioritizes practicality over novelty. The base network is a DenseNet-121, and the final layer is replaced with a 5-node fully-connected layer. We predict Diabetic Retinopathy classification in 5 separate stages.